4.5 Article

Rational Selection of the 3D Structure of Biomacromolecules for Molecular Docking Studies on the Mechanism of Endocrine Disruptor Action

期刊

CHEMICAL RESEARCH IN TOXICOLOGY
卷 29, 期 9, 页码 1565-1570

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.chemrestox.6b00245

关键词

-

资金

  1. National Natural Science Foundation of China [21507038, 21507061]
  2. Natural Science Foundation of Jiangsu Province [BK20150771, BK20151100]

向作者/读者索取更多资源

Molecular modeling has become an essential tool in predicting and simulating endocrine disrupting effects of chemicals. A key prerequisite for successful application of molecular modeling lies in the correctness of 3D structure for biomacromolecules to be simulated. To date, there are several databases that can provide the experimentally determined 3D structures. However, commonly, there are many challenges or disadvantageous factors, e.g., (a) lots of 3D structures for a given biomacromolecular target in the protein database; (b) the quality variability for those structures; (c) belonging to different species; (d) mutant amino acid residue in key positions, and so on. Once an inappropriate 3D structure of a target biomacromolecule was selected in molecular modeling, the accuracy and scientific nature of the modeling results could be inevitably affected. In this article, based on literature survey and an analysis of the 3D structure characterization of biomacromolecular targets belonging to the endocrine system in protein databases, six principles were proposed to guide the selection of the appropriate 3D structure of biomacromolecules. The principles include considering the species diversity, the mechanism of action, whether there are mutant amino acid residues, whether the number of protein chains is correct, the degree of structural similarity between the ligand in 3D structure and the target compounds, and other factors, e.g., the experimental pH conditions of the structure, determined process and resolution.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据